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Align multiple ggplot2 graphs with a common x axis and different y axes, each with different y-axis labels.
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#' When plotting multiple data series that share a common x axis but different y axes, | |
#' we can just plot each graph separately. This suffers from the drawback that the shared axis will typically | |
#' not align across graphs due to different plot margins. | |
#' One easy solution is to reshape2::melt() the data and use ggplot2's facet_grid() mapping. However, there is | |
#' no way to label individual y axes. | |
#' facet_grid() and facet_wrap() were designed to plot small multiples, where both x- and y-axis ranges are | |
#' shared across all plots in the facetting. While the facet_ calls allow us to use different scales with | |
#' the \code{scales = "free"} argument, they should not be used this way. | |
#' A more robust approach is to the grid package grid.draw(), rbind() and ggplotGrob() to create a grid of | |
#' individual plots where the plot axes are properly aligned within the grid. | |
#' Thanks to https://rpubs.com/MarkusLoew/13295 for the grid.arrange() idea. | |
library(ggplot2) | |
library(grid) | |
library(dplyr) | |
#' Create some data to play with. Two time series with the same timestamp. | |
df <- data.frame(DateTime = ymd("2010-07-01") + c(0:8760) * hours(2), series1 = rnorm(8761), series2 = rnorm(8761, 100)) | |
#' Create the two plots. | |
plot1 <- df %>% | |
select(DateTime, series1) %>% | |
na.omit() %>% | |
ggplot() + | |
geom_point(aes(x = DateTime, y = series1), size = 0.5, alpha = 0.75) + | |
ylab("Red dots / m") + | |
theme_minimal() + | |
theme(axis.title.x = element_blank()) | |
plot2 <- df %>% | |
select(DateTime, series2) %>% | |
na.omit() %>% | |
ggplot() + | |
geom_point(aes(x = DateTime, y = series2), size = 0.5, alpha = 0.75) + | |
ylab("Blue drops / L") + | |
theme_minimal() + | |
theme(axis.title.x = element_blank()) | |
grid.newpage() | |
grid.draw(rbind(ggplotGrob(plot1), ggplotGrob(plot2), size = "last")) | |
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